Learning Choice Model Trees for Feature-Based Multi-Product Pricing: Exact Optimization and Field Evidence

arXiv:2609.16952 · math.OC, stat.ML · Submitted 2026-09-15 · Read on arXiv

math.OC, stat.ML

Submitted: 2026-09-15

Updated: 2026-09-15

License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/

Terminology

• Pruning — 23× in this paper · explained in 4 episodes
• Aggregation — 6× in this paper · explained in 1 episode
• Regret — 5× in this paper · explained in 3 episodes
• Ablation — 4× in this paper · explained in 1 episode
• Interpretability — 2× in this paper · explained in 15 episodes
• Personalization — 2× in this paper · explained in 2 episodes
• Additivity — 1× in this paper · explained in 1 episode
• Alignment — 1× in this paper · explained in 1 episode
• Ancillary Pricing Optimization — 1× in this paper
• Distillation — 1× in this paper · explained in 2 episodes
• Feature Engineering — 1× in this paper · explained in 3 episodes
• Parsimony — 1× in this paper · explained in 2 episodes
• Query Complexity — 1× in this paper · explained in 2 episodes
• Sparsity — 1× in this paper · explained in 4 episodes

Sources

• Choice Modeling and Pricing for Scheduled Services
• Regret Bounds and Experimental Design for Estimate-then-Optimize
• Optimal Online and Offline Algorithms for Contextual MNL with Applications to Assortment and Pricing

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